lint and type fixes

api/onnx_web/chain/result.py

@@ -39,20 +39,26 @@ class StageResult:
     def __len__(self) -> int:
         if self.arrays is not None:
             return len(self.arrays)
-        else:
+        elif self.images is not None:
             return len(self.images)
+        else:
+            raise ValueError("empty stage result")
 
     def as_numpy(self) -> List[np.ndarray]:
         if self.arrays is not None:
             return self.arrays
-
+        elif self.images is not None:
             return [np.array(i) for i in self.images]
+        else:
+            raise ValueError("empty stage result")
 
     def as_image(self) -> List[Image.Image]:
         if self.images is not None:
             return self.images
-
+        elif self.arrays is not None:
             return [Image.fromarray(np.uint8(i), shape_mode(i)) for i in self.arrays]
+        else:
+            raise ValueError("empty stage result")
 
 
 def shape_mode(arr: np.ndarray) -> str:

api/onnx_web/chain/upscale_bsrgan.py

@@ -6,7 +6,14 @@ import numpy as np
 from PIL import Image
 
 from ..models.onnx import OnnxModel
-from ..params import DeviceParams, ImageParams, Size, StageParams, UpscaleParams
+from ..params import (
+    DeviceParams,
+    ImageParams,
+    Size,
+    SizeChart,
+    StageParams,
+    UpscaleParams,
+)
 from ..server import ModelTypes, ServerContext
 from ..utils import run_gc
 from ..worker import WorkerContext
@@ -17,7 +24,7 @@ logger = getLogger(__name__)
 
 
 class UpscaleBSRGANStage(BaseStage):
-    max_tile = 64
+    max_tile = SizeChart.micro
 
     def load(
         self,

api/onnx_web/chain/upscale_swinir.py

@@ -6,7 +6,7 @@ import numpy as np
 from PIL import Image
 
 from ..models.onnx import OnnxModel
-from ..params import DeviceParams, ImageParams, StageParams, UpscaleParams
+from ..params import DeviceParams, ImageParams, SizeChart, StageParams, UpscaleParams
 from ..server import ModelTypes, ServerContext
 from ..utils import run_gc
 from ..worker import WorkerContext
@@ -17,7 +17,7 @@ logger = getLogger(__name__)
 
 
 class UpscaleSwinIRStage(BaseStage):
-    max_tile = 64
+    max_tile = SizeChart.micro
 
     def load(
         self,

api/onnx_web/diffusers/pipelines/panorama.py

@@ -43,7 +43,6 @@ logger = logging.get_logger(__name__)
 
 # inpaint constants
 NUM_UNET_INPUT_CHANNELS = 9
-NUM_LATENT_CHANNELS = 4
 
 DEFAULT_WINDOW = 32
 DEFAULT_STRIDE = 8
@@ -1215,7 +1214,7 @@ class OnnxStableDiffusionPanoramaPipeline(DiffusionPipeline):
             negative_prompt_embeds=negative_prompt_embeds,
         )
 
-        num_channels_latents = NUM_LATENT_CHANNELS
+        num_channels_latents = LATENT_CHANNELS
         latents_shape = (
             batch_size * num_images_per_prompt,
             num_channels_latents,

api/onnx_web/diffusers/utils.py

@@ -88,8 +88,8 @@ def expand_prompt(
     negative_prompt: Optional[str] = None,
     prompt_embeds: Optional[np.ndarray] = None,
     negative_prompt_embeds: Optional[np.ndarray] = None,
-    skip_clip_states: Optional[int] = 0,
-) -> "np.NDArray":
+    skip_clip_states: int = 0,
+) -> np.ndarray:
     # self provides:
     #   tokenizer: CLIPTokenizer
     #   encoder: OnnxRuntimeModel
@@ -144,6 +144,7 @@ def expand_prompt(
 
         last_state, _pooled_output, *hidden_states = text_result
         if skip_clip_states > 0:
+            # TODO: why is this normalized?
             layer_norm = torch.nn.LayerNorm(last_state.shape[2])
             norm_state = layer_norm(
                 torch.from_numpy(

api/onnx_web/params.py

@@ -14,6 +14,7 @@ Point = Tuple[int, int]
 
 
 class SizeChart(IntEnum):
+    micro = 64
     mini = 128  # small tile for very expensive models
     half = 256  # half tile for outpainting
     auto = 512  # auto tile size
@@ -201,7 +202,7 @@ class ImageParams:
     batch: int
     control: Optional[NetworkModel]
     input_prompt: str
-    input_negative_prompt: str
+    input_negative_prompt: Optional[str]
     loopback: int
     tiled_vae: bool
     unet_tile: int
@@ -257,7 +258,7 @@ class ImageParams:
     def do_cfg(self):
         return self.cfg > 1.0
 
-    def get_valid_pipeline(self, group: str, pipeline: str = None) -> str:
+    def get_valid_pipeline(self, group: str, pipeline: Optional[str] = None) -> str:
         pipeline = pipeline or self.pipeline
 
         # if the correct pipeline was already requested, simply use that

api/onnx_web/utils.py

@@ -20,7 +20,7 @@ SAFE_CHARS = "._-"
 
 def split_list(val: str) -> List[str]:
     parts = [part.strip() for part in val.split(",")]
-    return [part for part in parts if len(part.strip()) > 0]
+    return [part for part in parts if len(part) > 0]
 
 
 def base_join(base: str, tail: str) -> str:
@@ -75,13 +75,13 @@ def get_from_list(
 
 
 def get_from_map(
-    args: Any, key: str, values: Dict[str, TElem], default: TElem
+    args: Any, key: str, values: Dict[str, TElem], defaultKey: str
 ) -> TElem:
-    selected = args.get(key, default)
+    selected = args.get(key, defaultKey)
     if selected in values:
         return values[selected]
     else:
-        return values[default]
+        return values[defaultKey]
 
 
 def get_not_empty(args: Any, key: str, default: TElem) -> TElem:
@@ -209,6 +209,8 @@ def load_config(file: str) -> Dict:
         return load_yaml(file)
     elif ext in [".json"]:
         return load_json(file)
+    else:
+        raise ValueError("unknown config file extension")
 
 
 def load_config_str(raw: str) -> Dict:

api/pyproject.toml

@@ -9,7 +9,9 @@ skip_glob = ["*/lpw.py"]
 [tool.mypy]
 # ignore_missing_imports = true
 exclude = [
-    "onnx_web.diffusers.lpw_stable_diffusion_onnx"
+    "onnx_web.diffusers.pipelines.controlnet",
+    "onnx_web.diffusers.pipelines.lpw",
+    "onnx_web.diffusers.pipelines.pix2pix"
 ]
 
 [[tool.mypy.overrides]]
@@ -27,8 +29,10 @@ module = [
     "compel",
     "controlnet_aux",
     "cv2",
+    "debugpy",
     "diffusers",
     "diffusers.configuration_utils",
+    "diffusers.image_processor",
     "diffusers.loaders",
     "diffusers.models.attention_processor",
     "diffusers.models.autoencoder_kl",
@@ -44,6 +48,7 @@ module = [
     "diffusers.pipelines.pipeline_utils",
     "diffusers.pipelines.stable_diffusion",
     "diffusers.pipelines.stable_diffusion.convert_from_ckpt",
+    "diffusers.pipelines.stable_diffusion_xl",
     "diffusers.schedulers",
     "diffusers.utils.logging",
     "facexlib.utils",
@@ -56,6 +61,11 @@ module = [
     "mediapipe",
     "onnxruntime",
     "onnxruntime.transformers.float16",
+    "optimum.exporters.onnx",
+    "optimum.onnxruntime",
+    "optimum.onnxruntime.modeling_diffusion",
+    "optimum.pipelines.diffusers.pipeline_stable_diffusion_xl_img2img",
+    "optimum.pipelines.diffusers.pipeline_utils",
     "piexif",
     "piexif.helper",
     "realesrgan",